Augmented collisional ionization via excited states in XUV cluster interactions

The impact of atomic excited states is investigated via a detailed model of laser-cluster interactions, which is applied to rare gas clusters in intense femtosecond pulses in the extreme ultraviolet (XUV). This demonstrates the potential for a two-step ionization process in laser-cluster interactions, with the resulting intermediate excited states allowing for the creation of high charge states and the rapid dissemination of laser pulse energy. The consequences of this excitation mechanism are demonstrated through simulations of recent experiments in argon clusters interacting with XUV radiation, in which this two-step process is shown to play a primary role; this is consistent with our hypothesis that XUV-cluster interactions provide a unique window into the role of excited atomic states due to the relative lack of photoionization and laser field-driven phenomena. Our analysis suggests that atomic excited states may play an important role in interactions of intense radiation with materials in a variety of wavelength regimes, including potential implications for proposed studies of single molecule imaging with intense X-rays.Comment: 4 pages, 2 figure

Shear stress induces osteogenic differentiation of human mesenchymal stem cells

Aim: To determine whether fluid flow-induced shear stress affects the differentiation of bone marrow-derived human mesenchymal stem cells (hMSCs) into osteogenic cells. Materials & methods: hMSCs cultured with or without osteogenic differentiation medium were exposed to fluid flow-induced shear stress and analyzed for alkaline phosphatase activity and expression of osteogenic genes. Results: Immediately following shear stress, alkaline phosphatase activity in osteogenic medium was significantly increased. At days 4 and 8 of culture the mRNA expression of bone morphogenetic protein-2 and osteopontin was significantly higher in hMSCs subjected to shear stress than those cultured in static conditions. However, hMSCs cultured in osteogenic differentiation medium were less responsive in gene expression of alkaline phosphatase and bone morphogenetic protein-2. Conclusion: These data demonstrate that shear stress stimulates hMSCs towards an osteoblastic phenotype in the absence of chemical induction, suggesting that certain mechanical stresses may serve as an alternative to chemical stimulation of stem cell differentiation

Development of a framework for metabolic pathway analysis-driven strain optimization methods

Genome-scale metabolic models (GSMMs) have become important assets for rational design of compound overproduction using microbial cell factories. Most computational strain optimization methods (CSOM) using GSMMs, while useful in metabolic engineering, rely on the definition of questionable cell objectives, leading to some bias. Metabolic pathway analysis approaches do not require an objective function. Though their use brings immediate advantages, it has mostly been restricted to small scale models due to computational demands. Additionally, their complex parameterization and lack of intuitive tools pose an important challenge towards making these widely available to the community. Recently, MCSEnumerator has extended the scale of these methods, namely regarding enumeration of minimal cut sets, now able to handle GSMMs. This work proposes a tool implementing this method as a Java library and a plugin within the OptFlux metabolic engineering platform providing a friendly user interface. A standard enumeration problem and pipeline applicable to GSMMs is proposed, making use by the community simpler. To highlight the potential of these approaches, we devised a case study for overproduction of succinate, providing a phenotype analysis of a selected strategy and comparing robustness with a selected solution from a bi-level CSOM.The authors thank the project “DeYeastLibrary—Designer yeast strain library optimized for metabolic engineering applications”, Ref. ERA-IB-2/0003/2013, funded by national funds through “Fundação para a Ciência e Tecnologia / Ministério da Ciência, Tecnologia e Ensino Superior”.info:eu-repo/semantics/publishedVersio

Stoichiometric representation of geneproteinreaction associations leverages constraint-based analysis from reaction to gene-level phenotype prediction

Genome-scale metabolic reconstructions are currently available for hundreds of organisms. Constraint-based modeling enables the analysis of the phenotypic landscape of these organisms, predicting the response to genetic and environmental perturbations. However, since constraint-based models can only describe the metabolic phenotype at the reaction level, understanding the mechanistic link between genotype and phenotype is still hampered by the complexity of gene-protein-reaction associations. We implement a model transformation that enables constraint-based methods to be applied at the gene level by explicitly accounting for the individual fluxes of enzymes (and subunits) encoded by each gene. We show how this can be applied to different kinds of constraint-based analysis: flux distribution prediction, gene essentiality analysis, random flux sampling, elementary mode analysis, transcriptomics data integration, and rational strain design. In each case we demonstrate how this approach can lead to improved phenotype predictions and a deeper understanding of the genotype-to-phenotype link. In particular, we show that a large fraction of reaction-based designs obtained by current strain design methods are not actually feasible, and show how our approach allows using the same methods to obtain feasible gene-based designs. We also show, by extensive comparison with experimental 13C-flux data, how simple reformulations of different simulation methods with gene-wise objective functions result in improved prediction accuracy. The model transformation proposed in this work enables existing constraint-based methods to be used at the gene level without modification. This automatically leverages phenotype analysis from reaction to gene level, improving the biological insight that can be obtained from genome-scale models.DM was supported by the Portuguese Foundationfor Science and Technologythrough a post-doc fellowship (ref: SFRH/BPD/111519/ 2015). This study was supported by the PortugueseFoundationfor Science and Technology (FCT) under the scope of the strategic fundingof UID/BIO/04469/2013 unitand COMPETE2020 (POCI-01-0145-FEDER-006684) and BioTecNorte operation (NORTE-01-0145FEDER-000004) fundedby EuropeanRegional Development Fund under the scope of Norte2020Programa Operacional Regional do Norte. This project has received fundingfrom the European Union’s Horizon 2020 research and innovation programme under grant agreementNo 686070. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Curiethérapie à débit pulsé des carcinomes du col utérin (expérience du Centre Oscar Lambret 1995-2003)

LILLE2-BU Santé-Recherche (593502101) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF